Higher-order EB method for the Incompressible Navier-Stokes Equations.
ORAL
Abstract
We present a higher-order embedded boundary (EB) method to solve partial differential equations in the presence of complex geometries for structured meshes.
We focus on the development and analysis of a new EB method that creates a water-tight grid via the divergence theorem, and uses cell/faces averages to achieve high order accuracy and stability for finite volume operators in the incompressible Navier-Stokes equations.
The method uses a novel weighted least squares approach to find the appropriate stencil coefficients for several operators to ensure conservation, accuracy, and stability in the presence of smooth and non-smooth geometries. We present results that verify the accuracy of the method, and use an eigenvalue analysis to demonstrate linear operator stability even with arbitrarily-small cut cells. Finally, we show the difference in accuracy between low-order and high-order results for simple and complex flow fields.
We focus on the development and analysis of a new EB method that creates a water-tight grid via the divergence theorem, and uses cell/faces averages to achieve high order accuracy and stability for finite volume operators in the incompressible Navier-Stokes equations.
The method uses a novel weighted least squares approach to find the appropriate stencil coefficients for several operators to ensure conservation, accuracy, and stability in the presence of smooth and non-smooth geometries. We present results that verify the accuracy of the method, and use an eigenvalue analysis to demonstrate linear operator stability even with arbitrarily-small cut cells. Finally, we show the difference in accuracy between low-order and high-order results for simple and complex flow fields.
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Presenters
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Oscar Antepara
Lawrence Berkeley National Laboratory
Authors
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Oscar Antepara
Lawrence Berkeley National Laboratory
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Hans Johansen
Lawrence Berkeley National Laboratory
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Nate Overton-Katz
Colorado State University
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Stephen Guzik
Colorado State University
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Daniel T Graves
Lawrence Berkeley National Laboratory
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Phillip Colella
Lawrence Berkeley National Laboratory